W. Lewis Johnson

Animated agents for procedural training in virtual reality: Perception, cognition, and motor control

This paper describes Steve , an animated agent that helps students learn to perform physical , procedural tasks . The student and Steve cohabit a three - dimensional , simulated mock - up of the students work environment . Steve can demonstrate how to perform tasks and can also monitor students while they practice tasks , providing assistance when needed . This paper describes Steves architecture in detail , including perception , cognition , and motor control . The perception module monitors the state of the virtual world , maintains a coherent representation of it , and provides this information to the cognition and motor control modules . The cognition module interprets its perceptual input , chooses appropriate goals , constructs and executes plans to achieve those goals , and sends out motor commands . The motor control module implements these motor commands , controlling Steves voice , locomotion , gaze , and gestures , allowing Steve to manipulate objects in the virtual world .

Intelligent Agents for Interactive Simulation Environments

■ Interactive simulation environments constitute one of today’s promising emerging technologies, with applications in areas such as education, manufacturing, entertainment, and training. These environments are also rich domains for building and investigating intelligent automated agents, with requirements for the integration of a variety of agent capabilities but without the costs and demands of low-level perceptual processing or robotic control. Our project is aimed at developing humanlike, intelligent agents that can interact with each other, as well as with humans, in such virtual environments. Our current target is intelligent automated pilots for battlefield-simulation environments. These dynamic, interactive, multiagent environments pose interesting challenges for research on specialized agent capabilities as well as on the integration of these capabilities in the development of “complete” pilot agents. We are addressing these challenges through development of a pilot agent, called TacAir-Soar, within the Soar architecture. This article provides an overview of this domain and project by analyzing the challenges that automated pilots face in battlefield simulations, describing how TacAir-Soar is successfully able to address many of them—TacAir-Soar pilots have already successfully participated in constrained air-combat simulations against expert human pilots—and discussing the issues involved in resolving the remaining research challenges.

Interactive pedagogical drama

This paper describes an agent-based approach to realizing interactive pedagogical drama. Characters choose their actions autonomously, while director and cinematographer agents manage the action and its presentation in order to maintain story structure, achieve pedagogical goals, and present the dynamic story to as to achieve the best dramatic effect. Artistic standards must be maintained while permitting substantial variability in story scenario. To achieve these objectives, scripted dialog is deconstructed into elements that are portrayed by agents with emotion models. Learners influence how the drama unfolds by controlling the intentions of one or more characters, who then behave in accordance with those intentions. Interactions between characters create opportunities to move the story in pedagogically useful directions, which the automated director exploits. This approach is realized in the multimedia title Carmen’s Bright IDEAS, an interactive health intervention designed to improve the problem solving skills of mothers of pediatric cancer patients.

Pedagogical agents on the Web

Animated pedagogical agents are lifelike animated characters that facilitate the learning process. This paper describes Adele, a pedagogical agent that is designed to work with Web-based educational simulations. The Adele architecture implements key pedagogical functions: presentation, student monitoring and feedback, probing questions, hints, and explanations. These capabilities are coupled with an animated persona that supports continuous multi-modal interaction with a student. The architecture supports client-side execution in a Web browser environment, and is able to inter-operate with simulations created by off-the-shelf authoring tools.

The politeness effect: Pedagogical agents and learning outcomes

Pedagogical agent research seeks to exploit Reeves and Nasss media equation theory, which holds that users respond to interactive media as if they were social actors. Investigations have tended to focus on the media used to realize the pedagogical agent, e.g., the use of animated talking heads and voices, and the results have been mixed. This paper focuses instead on the manner in which a pedagogical agent communicates with learners, i.e., on the extent to which it exhibits social intelligence. A model of socially intelligent tutorial dialog was developed based on politeness theory, and implemented in an agent interface within an online learning system called virtual factory teaching system. A series of Wizard-of-Oz studies was conducted in which subjects either received polite tutorial feedback that promotes learner face and mitigates face threat, or received direct feedback that disregards learner face. The polite version yielded better learning outcomes, and the effect was amplified in learners who expressed a preference for indirect feedback, who had less computer experience, and who lacked engineering backgrounds. These results confirm the hypothesis that learners tend to respond to pedagogical agents as social actors, and suggest that research should focus less on the media in which agents are realized, and place more emphasis on the agents social intelligence.

Serious Use of a Serious Game for Language Learning

The Tactical Language and Culture Training System (TLCTS) helps learners acquire basic communicative skills in foreign languages and cultures. Learners acquire communication skills through a combination of interactive lessons and serious games. Artificial intelligence plays multiple roles in this learning environment: to process the learners speech, to interpret and evaluate learner actions, to control the response of non-player characters, to generate hints, and to assess the trainees mastery of the skills. AI is also used in the authoring process to assist in the generation and validation of lesson content. This article gives an overview of the system, and describes the experience to date in transitioning the system from research prototype into a training system that is in regular use by tens of thousands of users in the United States and elsewhere. Experimental results from field studies are presented, relating learning outcomes, motivational effects, and the role of game-based learning and intelligent tutoring in achieving the learning outcomes.

Integrating Pedagogical Agents into Virtual Environments

In order for a virtual environment to be effective as a training tool, it is not enough to concentrate on the fidelity of the renderings and the accuracy of the simulated behaviors. The environment should help trainees develop an understanding of the task and should provide guidance and assistance as needed. This paper describes a system for developing virtual environments in which pedagogical capabilities are incorporated into autonomous agents that interact with trainees and simulations of objects in the environment. These pedagogical agents can monitor trainee progress and provide guidance and assistance. This paper describes the architectural features of the environment and of the agents that accomplish the instructional objectives within the virtual environment. It also discusses how agent-based instruction is combined with other methods of delivering instruction.

Integrating pedagogical capabilities in a virtual environment agent

Virtual environments are a promising milieu for education and training, because they allow students to practice their skills in 3D simulations of work settings. Autonomous agents can improve the eeectiveness of such e n vironments by assisting and collaborating with students as appropriate. This paper describes an autonomous pedagogical agent called Steve that can support the training of procedural skills such as operating or repairing complex equipment. Steves architecture permits him to sense and manipulate dynamic virtual worlds. The architecture also enables Steve to assume alternative realizations, either as a full, articulated, human gure or as abstract pointers and disembodied hands. Steve employs a combination of intelligent capabilities in his interactions with students and the environment: plan revision and execution, explanation, and student monitoring. These capabilities are employed in multiple ways in order to support alternative pedagogical styles. Steves knowledge representation is designed so that agent capabilities can be authored without detailed knowledge of agent architectures and languages.

Utilizing Scenarios in the Software Development Process

Abstract Scenarios play an important role throughout the information system development process. Scenarios are partial descriptions of system and environment behavior arising in restricted situations . They are instrumental to the following activities: describing and clarifying the relevant properties of the application domain, uncovering system requirements, evaluating design alternatives, and validating designs. This paper will describe these roles in the context of an example and explain how computer-based tools can support the use of scenarios throughout the development process. The thesis of this paper is based on experience with three such computer-based tools.

Tactical Language and Culture Training Systems: Using AI to Teach Foreign Languages and Cultures

The Tactical Language and Culture Training System (TLCTS) helps people quickly acquire communicative skills in foreign languages and cultures. More than 40,000 learners worldwide have used TLCTS courses. TLCTS utilizes artificial intelligence technologies during the authoring process, and at run time to process learner speech, engage in dialog, and evaluate and assess learner performance. This paper describes the architecture of TLCTS and the artificial intelligence technologies that it employs, and presents results from multiple evaluation studies that demonstrate the benefits of learning foreign language and culture using this approach.